Autism Spectrum Disease (ASD) is one of the most common heritable neuropsychiatric diseases with a worldwide prevalence of 1% (Kogan 2007) and over 90% heritability (Abrahams, 2008). The genetic and phenotypic variability in ASD remains one of the chief challenges in determining the causes of ASD (Schaaf, 2011). ASD is highly pleomorphic (Betancur, 2011), further, studies suggests that genetic variability may cause the behavioral variability seen in ASD (Happe, 2006). Given the uncertain etiology of ASD, parallel approaches are required to advance our understanding of the underlying biology of ASD. In addition to large genomic studies conducted with high throughput sequencing (HTS), neurobiological methods such as functional magnetic resonance imaging (fMRI) and other behavioral probes will be necessary to obtain better characterized patient cohorts. Understanding the genetic basis of ASD will contribute to the diagnosis and treatment of ASD. Approach: We propose to study ASD using two methods: HTS and neuro-behavioral phenotyping of ASD probands. In AIM #1 we will use hierarchical methods to analyze rare variants from 2000 cases and controls from the National Institutes of Mental Health (NIMH) that are undergoing exome capture and sequencing on SOLiD (Life Technologies, 2011) and Illumina (Illumina Inc, 2011) sequencers at Baylor College of Medicine and the Broad Insitute. We expect that methods developed to analyze large-scale exome studies in complex disease will be widely applicable to other studies. In AIM #2, we utilize functional magnetic resonance imaging (fMRI) and game theoretic reward, neuroeconomic, and interpersonal tasks to develop quantitative imaging and behavioral biomarkers (endophenotypes) for ASD probands. These subjects are currently being recruited at BCM and at Virginia Tech Carilion Research Institute. 50 trios (parents + proband) will be evaluated to examine segregation of endophenotypes. Unsupervised classification will also be utilized to identify endophenotype clusters for unrelated probands. In AIM #3, we utilize HTS to identify variants associated with endophenotype clusters identified in AIM #2. If these methods prove useful in identifying new genetic variants in ASD, we expect to rapidly expand the approach to other psychopathologies.